Visual searches are the new way people look for products on e-commerce websites or mobile apps. Traditionally, customers need to type long-tail keywords, for example- Nike red running shoes for men, which consumes time and chances are the results are different from expectations. If looking for an exact product, this took a lot of work.
Therefore, to provide convenience for product discovery, e-commerce companies like Amazon, Ikea, and eBay introduced a new feature called Visual Search, driven by AI. Customers loved this feature as it resolves the conventional challenges when searching for exact products. Studies show more than 36% of consumers have used visual search while shopping online.
Hence, in this blog, we will talk about AI-driven visual search, how it works, and how it helps customers search and discover products and e-commerce companies increase their revenue. So, without more delay, let’s get started.
What is AI-Driven Visual Search?
Let’s start by understanding the AI-driven visual search that enhances the product discovery process.
AI-powered visual search is a feature in e-commerce apps and websites that allows users to find products using images instead of text. It leverages artificial intelligence and machine learning capabilities to identify the exact and similar-looking products from e-commerce’s large databases.
AI-driven visual search offered by the Ikea website.
Read the next section to understand how AI-driven visual search works, in detail.
How Does AI-Enabled Visual Search Work?
The AI-driven visual search typically works as follows:
- Image Upload: A user clicks the image and uploads it into the feature.
- Image Recognition: The AI and machine learning algorithms evaluate the image uploaded by the user. It extracts the primary characteristics of the product such as shape, color, texture, brand logo (if visible), and more.
- Matching Algorithms: The AI systems in the feature compare the extracted characteristics with the product images and metadata stored in databases. It identifies the exact products and similar ones that exactly or closely match the extracted characteristics.
- Search Results: The e-commerce mobile app or website shows product results that are the same as the image and also similar products depending on the number of characteristics that match.
The visual search helps users especially when they do not know the name or details of the product they are looking for.
Benefits of AI-powered Visual Search in E-commerce
Here are the top benefits of AI-powered visual search in e-commerce for customers and e-commerce businesses.
Benefits for Customers
- Better User Experience
The AI-powered visual search allows users to find products by uploading images, reducing the need to know product names and details. This makes the search process better and enhances user experience.
- Improved Product Discovery
When AI-enable visual search shows product details, it also provides similar products that users might not have initially considered, but may like or buy.
Similar product results on the Puma website when searching for “Mens Sneakers”
- Accurate Search Results
The artificial intelligence algorithms focus on visual attributes from the image uploaded by the customer, to provide the exact or similar products. This eliminates irrelevant results and enhances the accuracy rate of search results.
- Convenience
AI-driven visual search allows users to search for products by simply clicking or uploading the image from their device’s camera, providing a high level of convenience to the customers.
- Personalization
AI-enabled visual search in the e-commerce tailors product recommendations based on visual preferences, delivering enhanced personalized shopping experiences to customers.
Benefits for E-commerce Companies
- Higher Conversion Rates
AI-driven visual search shows the exact or similar products users are looking for.
This increases the chances of customers buying the products, benefitting e-commerce businesses with high conversion rates.
- Increase Engagement
Customers prefer AI-enabled visual search when it comes to searching for products on e-commerce platforms.
It provides convenience, saves time, and shows relevant products, keeping customers on the platform for a long time.
- Improved Inventory Management
AI-driven visual search in e-commerce helps businesses understand which products are searched frequently.
Therefore, it helps e-commerce businesses manage their inventories with frequently searched products and their similar-looking ones.
- Data Insights
E-commerce businesses get data insights into the types of products searched using an AI-powered visual search feature.
Businesses use these insights to optimize their marketing strategies to attract customers and enhance sales.
- Competitive Advantage
Visual search powered by artificial intelligence is a novel feature in the e-commerce industry, and not so many companies are providing it.
Therefore, businesses that offer it to cater the modern consumer preferences, have a competitive advantage over the e-commerce companies that do not.
Therefore, integrating an AI-enabled visual search is a win-win for both customers and e-commerce businesses. Now, read further to learn how to integrate the visual search feature into the e-commerce website or mobile app.
How to Develop AI-Driven Visual Search For an E-Commerce Platform
In this section, you will learn about the development process of AI-driven visual search for an e-commerce app or website.
- Define Objectives and Use Cases
First, you need to determine the objectives of integrating visual search into your e-commerce platform. You need to plan whether the feature is for providing recommendations, increasing sales, or both.
If you want to provide product recommendations, you can develop algorithms that analyze images and show similar-looking products.
On the other side, if you want to increase sales, you can build algorithms to show the exact product by analyzing the product image provided by customers.
- Collect and Prepare Data
After defining the objectives, you need to prepare the image dataset. Collect high-quality images of products you sell on the e-commerce platform.
Also, label these images with relevant metadata. Metadata for images includes information about product images, such as product type, color, size, texture, and more.
- Develop the Visual Search Model
Once you have images, start developing the AI-powered visual search model for the e-commerce platform. Developing a visual search model, so you can hire top AI developers to help you with it.
To extract visual features from the images uploaded by customers, you can use Convolutional Neural Networks (CNNs), and pre-trained models like VGG16, ResNet, or Inception to fine-tune your dataset.
Moreover, you need to implement similarity metrics, such as cosine similarity and Euclidean distance, to compare features of products. Also, you can leverage tools like Faiss or Annoy for efficient similarity search.
*Please note that the tools mentioned here are recommendations only.
- Integrate the Model with Your Platform
Post development, it’s time to integrate the AI-enabled visual search with your e-commerce platform.
You need to develop APIs (application programming interfaces) that will handle the image uploads, process them, and return search results.
Moreover, you must create an intuitive interface to allow users to upload images and view results.
- Optimize and Scale
To improve speed, you can use techniques, such as model quantization or pruning to reduce model size.
Moreover, you must ensure that your infrastructure can handle high volumes of image uploads and searches.
- Testing and Quality Assurance
Before deploying the AI-enabled visual search, conduct user testing to get feedback and make necessary changes.
Also, evaluate its accuracy to check whether it is showing relevant results, and refine the algorithms if required.
- Deployment and Monitoring
Once testing is completed, deploy the AI-enabled visual search for the e-commerce platform.
However, do not forget to set up monitoring to track system performance, user engagement, and feedback.
- Upgrade the Visual Search
The job doesn’t finish with the deployment. You must update the model frequently with new data, images, and algorithm enhancements.
Also, prevent the model with more data so that accuracy does not get affected.
Moreover, check user feedback and address their issues by making necessary changes in the AI-enabled visual search for the e-commerce platform.
Therefore, this is how you can develop and integrate AI-driven visual search in your e-commerce platform.
AI Development Services
Real-World E-Commerce Business Using AI-Enabled Visual Search
The following are some of the leading e-commerce businesses that use AI-enabled visual search to enhance product discovery, customer engagement, sales, and more.
- Amazon
Source: Mike Mareen / Shutterstock.com
Amazon is one of the leading e-commerce companies that provides AI-driven visual search in their apps and websites. Known as Amazon StyleSnap, the visual search provides recommendations for similar products.
It leverages deep learning algorithms to match product characteristics with the image uploaded by customers on the Amazon platform.
- ASOS
Source: Heepsy
Online clothing and fashion e-commerce business, ASOS offers a user-friendly visual search tool that lets users take photos or upload images of clothing and accessories they like.
The tool then leverages AI algorithms to find and provide similar items available on ASOS, making it easier for customers to buy their favorite fashion articles.
- Wayfair
Source: Scott Olson/Getty Images
The home goods retailer Wayfair offers a visual search feature in its mobile app. The feature enables customers to take or upload photos of furniture and home decor and find similar products available on Wayfair, enhancing the furniture shopping experience.
- H&M
Source: Nedap Retail
H&M is one of the most popular clothing brands in the world. Its mobile application has an AI-driven visual search feature to provide convenience to customers looking for clothes and accessories.
Customers upload pictures and the tool searches for items in H&M’s catalog, making it easier for users to find and purchase products.
- eBay
Source: John G Mabanglo/EPA, via Shutterstock
eBay’s mobile application also has an AI-powered image search feature. Users upload pictures of items they are looking for, and the feature helps them by quickly locating the exact and similar products.
The Future of AI-Powered Visual Search
With innovations and technological advancements, the future of AI-enabled visual search would look like as follows:
- Better Accuracy and Fast Results
In the future, AI developers will use novel technologies to create advanced algorithms to power visual searches. These advanced algorithms will speed up the product analysis process and give results faster with greater accuracy.
- Visual Search In New Industries
Right now, AI-driven visual search is used majorly in the e-commerce industry. However, in the coming years, it is expected that other industries such as food, automobiles, manufacturing, and others, will adopt AI-powered visual search to enhance customer satisfaction and sales.
- Integration With Other Technologies
As we move forward, we will witness other technologies integrated into the visual search. Technologies like augmented reality and virtual assistants will enhance the functionalities of AI-enabled visual search and provide an elevated customer experience.
Conclusion
AI-driven visual search is a great feature when it comes to searching for products on the e-commerce platform. It offers great convenience to users as they only need to upload pictures of products they are looking for.
The visual search leverages artificial intelligence and machine learning algorithms to match the image with the products stored on the e-commerce platform database, and shows the exact and similar products to users.
For businesses, it is beneficial to integrate AI-powered visual search in e-commerce because it helps increase sales by showing similar products that users may like and buy.
Therefore, get your e-commerce platform equipped with an AI-enabled visual search by contacting Quytech, a leading artificial intelligence development company that has helped numerous startups and mid and large-sized businesses by delivering them top-notch AI solutions.
For more information, please visit: www.quytech.com